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257results about How to "Increase loyalty" patented technology

Real-time intelligent analysis and management system for customer credit self-evaluation factory

The invention discloses a real-time intelligent analysis and management system for a customer credit self-evaluation factory. The real-time intelligent analysis and management system comprises an engineering review module, a sales module, an intelligent production management module, a transportation management module, a material supply management module, a financial management module, a data management module, an intelligent analysis module, a server and a system terminal. The invention belongs to the technical field of factory management, and particularly provides a method for monitoring theoperation state of a factory in real time based on a big data platform, making it easier for a user to issue an order according to an analysis result and in combination with an actual production demand through intelligent analysis, and realizing handheld intelligent life. The credit rating and score of the user are intelligently self-evaluated; the customer credit self-evaluation factory real-timeintelligent analysis and management system performs multi-terminal operation, electronically and automatically collects information data of a factory operation process, analyzes various data of a factory through intelligent operation of an intelligent analysis engine, grasps intelligent operation of key factors, matches industry standard values, analyzes reasons and provides suggestions.
Owner:瑞熙(苏州)智能科技有限公司

Self-adaptive dynamic optimization method for bus dispatching timetable

The invention discloses a self-adaptive dynamic optimization method for a bus dispatching timetable. The optimization method comprises the following steps: determining full-day work time period T of a bus route I, rated passenger-carrying capacity C and maximum passenger-carrying capacity Cs of a bus service vehicle as well as bus departure interval tm; determining section passenger flow Pijlk distribution condition of the bus route I between the station i and the adjacent station j at the k time period; according to the matching of the section passenger flow data Pijlk (1) of the first bus fed back in real time in the running process of the bus route I between the station i and the adjacent station j and the history bus station passenger flow section accumulated distribution curve, predicating section passenger flow demand distribution condition Pijlk (2) of the second bus, and determining the bus departure time T12 of the second bus; and determining the bus dispatching timetable of the bus route I in the full-day work time period T by utilizing a recurrence method. According to the he self-adaptive dynamic optimization method, the bus dispatching time can be dynamically adjusted by self-adapting the bus dispatching timetable, thereby meeting the ever-changing passenger flow demands, enhancing the reliability of the bus service, reducing bus driving delay, and improving bus service satisfaction level.
Owner:SOUTHEAST UNIV

Internet of things based personal self-help parking charge management system

An internet of things based personal self-help parking charge management system comprises a mobile terminal, a server, an internet of things parking lock, a server management terminal, system maintenance staff, and park management staff, which interact with one another; the mobile terminal is used for installing APP (application) software and remotely controlling the internet of things parking lock and is connected to a third-party payment platform to allow mobile payment; the server is used for running the APP software in the system; the internet of things parking lock comprises a parking lock; a control circuit connectable to the internet is built in the internet of things parking lock and is connected with a mobile broadband network and used for receiving a control signal from the mobile terminal so as to lock or unlock a parking lot and sending idleness / occupation information of the parking lot to the server; the system maintenance staff is used for maintaining, correcting and managing the information and data stored in the server and a park management terminal; the park management staff is used for managing and monitoring a park. The system has the advantages that the problems such that the existing owners of cars in cities have difficulties in parking the cars and finding parking lots and payment is time consuming are comprehensively solved through the wireless internet and a simplest method, and the system is of good social benefit.
Owner:达富科技(厦门)有限公司

Two-dimensional code-based data analysis anti-counterfeiting traceability marketing management method and system

The invention provides a two-dimensional code-based data analysis anti-counterfeiting traceability marketing management method and system. After a two-dimensional code of a product is scanned, whether the two-dimensional code of the product is scanned for the first time or not can be judged; when the judgment result is negative, a consumer can be reminded that the product can be a counterfeited product; and the consumer can conveniently and accurately know the authenticity of the purchased product. A point exchange platform, an awarding platform, a game platform, a big data platform, an O2O mall and logistics platform and a wechat public account are also constructed. After the consumer purchases the product, the consumer is stimulated employing anti-counterfeiting tracing as an entry in manners of presenting points, participating in game raffling and the like; the consumer interacts with an enterprise, so that the viscosity of the consumer is strengthened; the loyalty index is improved; the range of the consumer group is expanded; when the consumer participates in interaction, the system collects large data of the consumer, carries out data mining and analysis, provides a big data support for the enterprise, draws a portrait of the consumer, and carries out accurate precision marketing and secondary product marketing.
Owner:广西天海信息科技有限公司

Application of multi-supporting-degree positive and negative sequence modes in clients' purchasing behavior analysis

The invention relates to application of multi-supporting-degree positive and negative sequence modes in clients' purchasing behavior analysis. An efficient algorithm named as E-ms NSP is provided to excavate the multi-supporting-degree based positive and negative sequence modes, the main idea of the algorithm is that firstly an improved MS-GSP algorithm is adopted to excavate the multi-supporting-degree based positive sequence mode, then a method the same as e-NSP is adopted to calculate the supporting degree of a negative sequence candidate mode through a formula, and database re-scanning is not needed. The E-ms NSP is a first multi-supporting-degree based negative sequence mode excavation algorithm without constraint limitation. In application, commodities large in clients' purchasing volume of each category of products are screened out within a certain time period, so that when clients purchase the products, certain similar relevant products high in clients' purchasing frequency can be recommended for others by utilizing the multi-supporting-degree positive and negative sequence modes, transaction opportunities of the clients are increased, website browsers are changed into purchasers, cross-selling capacity is improved, the loyalty index of the clients is improved, and the economic benefit of websites is improved.
Owner:SHANDONG EVAYINFO TECH CO LTD

Queueing time estimation method

InactiveCN101540016AThe waiting time is accurateIncrease profitChecking apparatusDistribution functionUtilization rate
The invention relates to a queueing time estimation method for estimating the queueing time of clients in a service system. The queueing time estimation method includes the steps of client classification and providing queueing time probability distribution functions of various clients; when more than five clients wait, the attributes of the clients being served and the clients to be served are respectively checked, and the corresponding queueing time probability distribution function is generated; the number of the left clients is estimated according to the function, and the queueing time is estimated according to the number of the left clients and is provided for the clients; and when less than five clients wait, the queueing time of maximum probability of the clients to be served is added to obtain the queueing time of the clients directly according to the queueing time probability distribution function. The number of the left clients is estimated through the client classification and the probability distribution functions, and the estimated service queueing time can be more accurately provided for the clients compared with the prior art; and based on the estimated service queueing time provided for the clients, the utilization rate of the queueing time can be improved by the clients, and the trust, the satisfaction and the loyalty for the service quality of service improvers can be improved by the clients.
Owner:SHENZHEN AOTO ELECTRONICS

System for automatically evaluating machine translation by using sentence structure information and implementing method

The invention discloses a method for automatically evaluating machine translation, which comprises the following steps: reading machine translated text obtained by the machine translation, sentence structure related marking information of the machine translated text and a source language sentence; reading the sentence structure related marking information of the source language sentence, the reference translated text of the source language sentence and the sentence structure related marking information of the reference translated text according to the source language sentence; analyzing the sentence structure of the machine translated text, analyzing the sentence structure of the source language sentence, and analyzing the sentence structure of the reference translated text; comparing the sentence structure of the source language sentence with the sentence structure of the reference translated text, and calculating the conversion condition of the sentence structure of the reference translated text; and comparing the sentence structure of the source language sentence with the sentence structure of the machine translated text, calculating the conversion condition of the sentence structure of the machine translated text, then comparing the conversion condition of the sentence structure of the reference translated text with the conversion condition of the sentence structure of the machine translated text, and evaluating the machine translated text according to the comparison result.
Owner:INST OF ACOUSTICS CHINESE ACAD OF SCI

Method for quickly applying negative sequence mining patterns to customer purchasing behavior analysis

The invention provides a method for quickly applying negative sequence mining patterns to customer purchasing behavior analysis. A fast algorithm named as f-NSP is proposed to efficiently mine the negative sequential patterns. According to the main idea of the algorithm, firstly, a positive sequential pattern is obtained through a positive sequential pattern mining algorithm, and as for all frequent positive sequences, an efficient bitmap storage structure is used for storing data sequences including the frequent positive sequences; secondly, negative candidates are generated through a method which is the same as e-NSP and is used for generating negative candidate sequences; finally, data bitmaps are subjected to and operation, or operation and xor operation by means of a formula, the support degree of the negative candidates is quickly calculated, the negative sequential pattern meeting the minimum support degree is mined, and a database does not need to be scanned again. Purchasing behaviors of customers are analyzed through screened sequential patterns so that a seller can predict subsequent commodity buying and selling conditions according to current commodity buying and selling conditions; as a result, the seller can arrange placement of commodities better, and the sale quantity of the commodities can be increased.
Owner:QILU UNIV OF TECH
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